Discriminative hidden kalman filters for classification of streaming sensor data in condition monitoring
US-2015142384-A1 · May 21, 2015 · US
US12585255B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12585255-B2 |
| Application number | US-201816143305-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 26, 2018 |
| Priority date | May 9, 2016 |
| Publication date | Mar 24, 2026 |
| Grant date | Mar 24, 2026 |
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Methods and systems for a monitoring system for data collection in an industrial environment including a data collector communicatively coupled to a plurality of input channels connected to data collection points operationally coupled to at least one industrial component in at least one of an industrial boiler system or industrial pipeline system; a data storage structured to store a library of stored noise patterns associated with operation of the at least one industrial component; a data acquisition circuit structured to interpret a plurality of detection values from the collected data; and a data analysis circuit structured to: analyze the collected data, determine a measured noise pattern for the at least one industrial component, and compare the measured noise pattern to the library of stored noise patterns to identify a changed condition of the at least one industrial component.
Opening claim text (preview).
What is claimed is: 1 . A monitoring system for data collection in an industrial environment, the system comprising: a data collector electrically coupled to a plurality of data input channels electrically connected to data collection points operationally coupled to at least one industrial component in at least one of an industrial boiler system or an industrial pipeline system, the data collection points being configured to collect data and electrically transmit the collected data to the data collector via the plurality of data input channels; a data storage structured to store a library of stored noise patterns associated with operation of the at least one industrial component, the library of stored noise patterns being from a noise pattern data market, the noise pattern data market comprising a self-organizing data marketplace for industrial IoT noise pattern data; a data acquisition circuit in electronic communication with the data collector and structured to interpret a plurality of detection values from collected data, each of the plurality of detection values corresponding to at least one of the plurality of data input channels; and a data analysis circuit in electronic communication with the data acquisition circuit and structured to: analyze the collected data; determine a measured noise pattern for the at least one industrial component; and compare the measured noise pattern to the library of stored noise patterns to identify a changed condition of the at least one industrial component. 2 . The system of claim 1 , wherein the library of stored noise patterns comprises a plurality of noise patterns corresponding to a plurality of associated states of the at least one industrial component. 3 . The system of claim 2 , wherein the data analysis circuit further comprises at least one of a rule-based expert system or a model-based expert system to identify changes in the measured noise pattern. 4 . The system of claim 3 , wherein the data analysis circuit is further structured to seed the at least one of the rule-based expert system or the model-based expert system using the library of stored noise patterns. 5 . The system of claim 1 , wherein the data analysis circuit utilizes a noise pattern analysis to determine if the measured noise pattern matches a noise pattern of a second industrial component stored in the library of stored noise patterns. 6 . The system of claim 1 , wherein the library of stored noise patterns uses a distributed ledger to store transactional data. 7 . The system of claim 1 , wherein the data analysis circuit utilizes a noise pattern analysis to identify the changed condition. 8 . A computer-implemented method for data collection in an industrial environment, the method comprising: collecting data via a data collector electrically coupled to a plurality of data input channels, the plurality of data input channels being electrically connected to data collection points operationally coupled to at least one industrial component in at least one of an industrial boiler system or an industrial pipeline system, the data collection points electrically transmitting the collected data to the data collector via the plurality of data input channels; receiving a library of stored noise patterns from a noise pattern data market, the noise pattern data market comprising a self-organizing data marketplace for industrial IoT noise pattern data; storing the library of stored noise patterns in a data storage, the stored noise patterns being associated with operation of the at least one industrial component; interpreting a plurality of detection values from the collected data with a data acquisition circuit, each of the plurality of detection values corresponding to at least one of the plurality of data input channels; analyzing the collected data; determining a measured noise pattern for the at least one industrial component; comparing the measured noise pattern to the library of stored noise patterns to identify a changed condition of the at least one industrial component; and utilizing a noise pattern analysis to determine if the measured noise pattern matches a noise pattern of a second industrial component stored in the library of stored noise patterns. 9 . The method of claim 8 , further comprising using a distributed ledger to store transactional data relating to the library of stored noise patterns. 10 . The method of claim 8 , wherein the library of stored noise patterns comprises a plurality of noise patterns corresponding to a plurality of associated states of the at least one industrial component. 11 . The method of claim 8 , further comprising operating at least one of a rule-based expert system or a model-based expert system to identify the changed condition. 12 . An apparatus for monitoring data collection in an industrial environment, the apparatus comprising: a data collector electrically coupled to a plurality of data input channels electrically connected to data collection points operationally coupled to at least one industrial component in at least one of an industrial boiler system or an industrial pipeline system; a library of stored noise patterns received from a noise pattern data market, the noise pattern data market comprising a self-organizing data marketplace for industrial IoT noise pattern data; a data storage structured to store the library of stored noise patterns associated with operation of the at least one industrial component; a data acquisition circuit in electronic communication with the data collector and structured to interpret a plurality of detection values from collected data, each of the plurality of detection values corresponding to at least one of the plurality of data input channels; and a data analysis circuit in electronic communication with the data acquisition circuit and structured to: analyze the collected data; determine a measured noise pattern for the at least one industrial component; and compare the measured noise pattern to the library of stored noise patterns to identify a state value of the at least one industrial component, wherein the library of stored noise patterns uses a distributed ledger to store transactional data. 13 . The apparatus of claim 12 , wherein the library of stored noise patterns comprises a plurality of noise patterns corresponding to a plurality of associated states of the at least one industrial component. 14 . The apparatus of claim 12 , wherein the data analysis circuit utilizes a noise pattern analysis to determine if the measured noise pattern matches a noise pattern of a second industrial component stored in the library of stored noise patterns. 15 . The apparatus of claim 12 , wherein the data analysis circuit further comprises at least one of a rule-based expert system or a model-based expert system to identify the state value.
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